Shenyang Institute of Automation,Chinese Academy Of Sciences
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Vibration and Reliability Analysis of Non-Uniform Composite Beam under Random Load
No full textNon-uniform structures and composite materials have advantages in engineering appli-cations, such as light weight design, multi-functionality, and better buckling/flutter load capacity. For composite structures under dynamic loading conditions, reliability is a key problem to be analyzed during practical operations. However, there is little research work on non-uniform composite structural reliability analysis under random load. The forced vibration response of non-uniform composite beam under random load is firstly solved by the Adomian Decomposition Method (ADM) and iterative process for reliability analysis. Different variation laws of the cross-section rigidity and mass distribution along the length of the non-uniform composite beam structures are analyzed. Various angular frequency and amplitude of random base motion acceleration following Gaussian distribution are considered. Influences of different random excitations and structural design on vibration responses and reliability are studied. The larger mean and variance of excitation frequency leads to the smaller amplitude and strain of the beam, while greater mean and variance of the base motion excitation amplitude will induce the higher maximum amplitude and strain values and lower reliability. The influences of structural design on reliability are studied. The reliability increases with the increment of taper ratios of the host beam and composite layer. The iteration mathematical model and numerical solutions proposed in this paper can be used to solve and analyze vibration responses and reliability of general non-uniform composite beam structures under arbitrary excitation during a certain period of time.</p
Composition analysis of ceramic raw materials using laser-induced breakdown spectroscopy and autoencoder neural network
No full textIn the ceramic production process, the content of Si, Al, Mg, Fe, Ti and other elements in the ceramic raw materials has an important impact on the quality of the ceramic products. Exploring a method that can quickly and accurately analyze the content of key elements in ceramic raw materials is of great significance to improve the quality of ceramic products. In this work, laser-induced breakdown spectroscopy (LIBS) is used for rapid analysis of ceramic raw materials. The chemical element composition and content of ceramic raw materials are quite different, which leads to serious matrix effects. Building an artificial neural network model is an effective way to solve the complex matrix effects, but model training can easily lead to overfitting due to the high number of spectral features and the limited number of samples. In order to solve this problem, we propose a feature extraction method that combines the linear regression (LR) and the sparse and under-complete autoencoder (SUAC) neural network. This LR + SUAC method performs nonlinear feature extraction and dimension reduction on high-dimensional spectral data. The spectral data dimension is reduced from 8188 to 100 through the LR layer, and further reduced to 32 through the SUAC encoding layer. Further, a quantitative analysis model for the elemental composition of ceramic raw materials is established by the combination of LR + SUAC and Back Propagation Neural Network (BPNN). Since the input data dimension and redundant information are greatly reduced by LR + SUAC, the overfitting problem of BPNN is greatly reduced. Experiment results showed that the LR + SUAC + BPNN method obtained the best quantitative analysis performance compared with several other methods in the cross-validation process.</p
一种可适应变步频行走的步态相位识别方法
No full text本发明涉及一种可适应变步频行走的步态相位识别方法，通过将惯性测量单元放置在足部来采集人体运动数据；设计可依据步频、幅值特征进行结构参数自调整的足部极值检测算法，实现对足部运动数据极值点特征的稳定提取；设计融合自适应振荡器的足部零速检测算法，实现对足部零速状态特征的精确提取；利用有限状态机来对所提取的足部特征值进行归类分析，从而实现在变步频的行走模式下，对足部触地相、站立相、站立末相与预摆动相四个相位的精确识别。本发明使得对足部步态相位的识别过程不再局限于实验室环境下以及固定步频的行走模式，有效提升了复杂环境与运动模式下的步态相位识别准确度，有助于步态分析在医疗康复与康复机器人领域的应用与发展
多水下机器人最大探测覆盖率的快速梳型路径规划方法
No full text本发明涉及到多水下机器人路径规划技术领域，尤其设计一种多自主水下机器人基于探测区域覆盖率的路径规划方法。包括以下步骤：基于待探测区域的地形条件以及自主水下机器人的探测能力，构建二维栅格模型；基于二维栅格模型，采用分步迭代的方式确定单体自主水下机器人的探测轨迹，进而得到单体自主水下机器人进行梳型探测时的探测面积；利用单体自主水下机器人进行梳型探测时的探测面积，结合粒子群优化算法，得到满足多自主水下机器人最大探测覆盖率时的路径规划。本方法时刻计算自主水下机器人当前航线与所有登高线关系并确定安全的方法。使得规划更快速，适合海上不断变化的探测环境，具有很高的工程意义
一种基于功能自治模型的AUV控制软件体系结构
No full text本发明涉及一种基于功能自治模型的自主水下机器人(AUV)控制软件体系结构，该体系结构设计了针对AUV控制软件的功能模块划分方法，该方法采用使命任务与执行管理功能模块作为软件的思考层，并根据控制功能对控制软件进行功能自治模块划分，所得到的功能自治模块在功能上相对独立。同时在功能自治模块内部采用执行层和反应层的二层划分方法并设计低耦合度的功能模块协作方法,使控制软件体系结构具有易扩展、易维护的特性；同时在控制系统体系结构底层采用操作系统功能封装方法得到不依赖操作系统的上层软件开发功能接口,使软件体系结构在不同操作系统间移植时具有良好的复用性和可移植性
非晶态带材高速切割装置
No full text本发明涉及非晶合金加工技术领域，具体地说是一种非晶态带材高速切割装置，包括输入滚轮、输入导向滚轮、水导激光耦合装置和多个输出滚轮，非晶态带材缠绕于输入滚轮上且一端伸出并依次绕过各个输入导向滚轮后进入加工工位，发射水导激光的水导激光耦合装置设于加工工位上方，且所述非晶态带材通过水导激光分割成多条，并且每条非晶态带材缠绕于对应的输出滚轮上。本发明利用水导激光加工技术对非晶态带材进行精密加工，大大提高了非晶态带材的加工精度及加工效率
一种螺母自动上料机构
No full text本发明涉及自动化工业生产线的自动拧紧设备，特别涉及一种螺母自动上料机构。该机构包括螺母供顶机、螺母定位机构及螺母拾取机构，其中螺母供顶机通过螺母供顶机长直振将螺母自动有序的排列；螺母定位机构设置于螺母供顶机长直振的端部，用于对螺母供顶机长直振输送的螺母进行定位；螺母拾取机构设置于螺母供顶机上，且位于螺母定位机构的上方，螺母拾取机构用于拾取通过螺母定位机构定位的螺母。本发明实现了所有动作的自动化，将螺母出料、定位、拾取等动作进行了高度的集成，优化了结构，有效的解决了机构功能单一的问题，并降低了成本
一种火炬对接无人机
No full text本发明涉及无人机技术领域，特别涉及一种火炬对接无人机。包括旋翼无人机、机械臂、视觉引导系统及视觉定位系统，其中机械臂设置于旋翼无人机机身的下方，机械臂用于与目标火炬对接；视觉引导系统设置于旋翼无人机机身的正前方，视觉引导系统用于远距离检测目标火炬的位置；视觉定位系统设置于旋翼无人机的旋翼下方，视觉定位系统用于近距离检测目标火炬的位置。本发明可实现无人机在视觉引导系统引导下的大范围全自主火炬对接，机械臂在视觉定位系统驱动下的小范围精准火炬对接以及机械臂和火炬姿态不影响桨叶安全运行等功能
A non-interactive verifiable computation model of perceptual layer data based on CP-ABE
No full textThe computing of smart devices at the perception layer of the power Internet of Things is often insufficient, and complex computing can be outsourced to server resources such as the cloud computing, but the allocation process is not safe and controllable. Under special constraints of the power Internet of Things such as multi-users and heterogeneous terminals, we propose a CP-ABE-based non-interactive verifiable computation model of perceptual layer data. This model is based on CP-ABE, NPOT, FHE and other relevant safety and verifiable theories, and designs a new multi-user non-interactive secure verifiable computing scheme to ensure that only users with the decryption key can participate in the execution of NPOT Scheme. In terms of the calculation process design of the model, we gave a detailed description of the system model, security model, plan. Based on the definition given, the correctness and safety of the non-interactive safety verifiable model design in the power Internet of Things environment are proved, and the interaction cost of the model is analyzed. Finally, it proves that the CP-ABE-based non-interactive verifiable computation model for the perceptual layer proposed in this paper has greatly improved security, applicability, and verifiability, and is able to meet the security outsourcing of computing in the power Internet of Things environment
A method for obtaining the fraction of absorbed energy of material based on laser shock processing experiment and simulation
No full textFraction of absorbed energy (FAE) is an important parameter to determine the plasma shock wave pressure. With the purpose of obtaining the FAE of material and accurately calculating the plasma shock wave pressure, a method based on laser shock processing (LSP) experiment and finite element simulation was proposed in this work. The Ni-based superalloy GH4169 was selected as experimental material, and the experimental sample was treated by single-point LSP. The residual stress of experimental sample after LSP treatment was determined using sin2ψ method by X-ray residual stress device. In finite element simulation, the initial value of FAE was assumed as 0.1, and then, the LSP finite element simulation was performed with the change of FAE until the results obtained by LSP experiment and simulation were fell into an allowable range. Based on this method, the FAE with 0.13 for Ni-based superalloy GH4169 was obtained. This work can enrich the theory of LSP and provide theoretical guidance for researchers to obtain the accurate FAE of materials.</p